U.S. patent application number 10/845630 was filed with the patent office on 2004-12-16 for system and method for evaluating vehicle and operator performance.
Invention is credited to Hubbard, Jonathan, Kantarjiev, Christopher, Reid, Robert, Tash, Jonathan.
Application Number | 20040254698 10/845630 |
Document ID | / |
Family ID | 33479272 |
Filed Date | 2004-12-16 |
United States Patent
Application |
20040254698 |
Kind Code |
A1 |
Hubbard, Jonathan ; et
al. |
December 16, 2004 |
System and method for evaluating vehicle and operator
performance
Abstract
The present invention relates to the field of safety management
of one or more vehicles, and more particularly, to a system and
method for analyzing information relating to a vehicle's
performance characteristics such as speed against environmental
attributes such as speed limits to assess a vehicle and operator's
tendency to operate according to preset or other criteria.
Inventors: |
Hubbard, Jonathan; (San
Francisco, CA) ; Kantarjiev, Christopher; (Palo Alto,
CA) ; Reid, Robert; (Campbell, CA) ; Tash,
Jonathan; (Tucson, AZ) |
Correspondence
Address: |
CARR & FERRELL LLP
2200 GENG ROAD
PALO ALTO
CA
94303
US
|
Family ID: |
33479272 |
Appl. No.: |
10/845630 |
Filed: |
May 13, 2004 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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60471021 |
May 15, 2003 |
|
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60490199 |
Jul 25, 2003 |
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Current U.S.
Class: |
701/32.7 ;
701/1 |
Current CPC
Class: |
G08G 1/0104 20130101;
G08G 1/20 20130101; G08G 1/127 20130101 |
Class at
Publication: |
701/035 ;
701/001; 701/029 |
International
Class: |
G01M 017/00 |
Claims
What is claimed is:
1. A system for evaluating performance of a vehicle comprising: a
processor; an analysis engine configured to analyze data from a
database and generate an indication; a report generator configured
to generate evaluation information; a map database configured to
provide map data; and a vehicle/operator database configured to
provide vehicle/operator data.
2. The system of claim 1 further comprising a client for accessing
the processor.
3. The system of claim 2 wherein the evaluation information is
delivered to the client.
4. The system of claim 3 wherein delivery of the evaluation
information occurs over at least a network.
5. The system of claim 3 wherein the processor delivers the
evaluation information in response to a client request.
6. The system of claim 1 wherein the map data comprises at least
one road segment attribute associated with at least one road
segment.
7. The system of claim 1 further comprising a vehicle wherein
vehicle data is generated at the vehicle and transmitted via at
least one relay and a network to the processor.
8. The system of claim 7 wherein the vehicle data comprises vector
data.
9. The system of claim 7 wherein the vehicle data comprises
operational data.
10. A method for evaluating vehicle performance comprising:
retrieving map data from a map database; retrieving
vehicle/operator data from a vehicle/operator database; analyzing
the vehicle/operator data against the map data; and generating
evaluation information.
11. The method of claim 10 further comprising delivering evaluation
information.
12. The method of claim 11 wherein delivery of evaluation
information occurs over at least a network.
13. The method of claim 11 wherein delivery of evaluation
information occurs in response to a client request.
14. The method of claim 10 further comprising generating vehicle
data at a vehicle.
15. The method of claim 14 further comprising transmitting the
vehicle data to the processor.
16. A method for evaluating vehicle performance comprising:
generating vehicle data; transmitting the vehicle data to a
processor; retrieving map data from a map database; analyzing the
vehicle data against the map data; and generating evaluation
information.
17. The method of claim 16 wherein transmitting the vehicle data to
a processor occurs over at least a relay and a network.
18. The method of claim 16 further comprising delivering evaluation
information.
19. A method for evaluating vehicle performance comprising:
retrieving map data from a map database; attempting to retrieve
vehicle/operator data from a vehicle/operator database; determining
the vehicle/operator data is not available; requesting vehicle data
from a vehicle; transmitting the vehicle data to a processor;
analyzing the vehicle data against the map data; and generating
evaluation information.
20. The method of claim 19 wherein requesting vehicle data occurs
over at least a relay and a network.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] The present application claims the priority benefit of U.S.
Provisional Patent Application No. 60/471,021 entitled "Method and
System for Evaluating Performance of a Vehicle and/or Operator"
filed May 15, 2003 and U.S. Provisional Patent Application No.
60/490,199 entitled "System and Method for Determining and Sending
Recommended Departure Time Based on Predicted Traffic Conditions to
Road Travelers" filed Jul. 25, 2003. The disclosures of these
commonly owned and assigned applications are incorporated by
reference.
BACKGROUND OF THE INVENTION
[0002] 1. Field of the Invention
[0003] The present invention relates generally to the field of
safety management of one or more vehicles, and more particularly,
to analyzing information relating to a vehicle's performance
characteristics against map database attributes to assess a
vehicle's tendency to operate according to a set of criteria.
[0004] 2. Description of Related Art
[0005] The American trucking industry employs nearly ten million
people. This includes more than 3 million truck drivers who travel
over 400 billion miles per year to deliver to Americans 87% of
their transported food, clothing, finished products, raw materials,
and other items. Trucks are the only providers of goods to 75
percent of American communities, and for many people and businesses
located in towns and cities across the United States, trucking
services are the only available means to ship goods. As five
percent of the United States' Gross Domestic Product is created by
truck transportation, actions that affect the trucking industry's
ability to move its annual 8.9 billion tons of freight have
significant consequences for the ability of every American to do
their job well and to enjoy a high quality of life.
[0006] With the importance of the American trucking industry in
mind, it is unfortunate that workers in the American trucking
industry experience the most fatalities of all occupations,
accounting for twelve percent of all American worker deaths.
Approximately two-thirds of fatally injured truckers are involved
in highway crashes. Roughly 475,000 large trucks are involved in
crashes that result in approximately 5,360 fatalities and 142,000
injuries each year. Of these fatalities, about seventy-four percent
are occupants of other vehicles (usually passenger cars), three
percent are pedestrians, and twenty-three percent are occupants of
large trucks. As there was a twenty-nine percent increase between
the years of 1990 and 2000 in the number of registered large trucks
and a forty-one percent increase in miles traveled by large trucks,
it is evident that the risks involved in the trucking industry are
not simply going to go away. If anything, this increase in trucks
on the road and miles traveled evidences that the $3 billion in
lost productivity to the economy and hundreds of millions of
dollars in insurance premiums caused by truck crashes may get even
worse.
[0007] Studies and data indicate that driver errors and
unacceptable driver behaviors are the primary causes of, or primary
contributing factors to, truck-involved crashes. The Federal Motor
Carrier Safety Administration reports that speeding (i.e.,
exceeding the speed limit or driving too fast for conditions) is a
contributing factor in twenty-two percent of fatal crashes
involving a truck in 2000. Additionally, National Highway Traffic
Safety Administration reports that speeding is a contributing
factor in twenty-nine percent of all fatal crashes in 2000. More
than 12,000 people lost their lives in 2000 in part due to
speed-related crashes.
[0008] With the pressure of making on-time deliveries, many drivers
are willing to accept the risks of unsafe driving in order to
achieve timely arrivals. Unfortunately, the primary tool for
preventing unsafe driving--law enforcement--can only be present in
so many places at so many times. Even when law enforcement is
present, drivers can communicate with one another to inform them of
'speed traps' or other locales where law enforcement presence is
high. While drivers may engage in ultra-safe driving in these
areas, it does not change the fact that a vast majority of the time
these drivers are on the road, they are not subject to any type of
third-party supervision or accountability with regard to their
driving habits. Thus, additional oversight of driver behavior is
required.
[0009] Although causes of crashes are largely human, important
solutions may be found in technology to facilitate and augment
driver performance. For example, to minimize these costs,
conventional telemetric safety solutions are used to observe and
measure vehicle tendencies and patterns for improving safety.
Generally, these solutions are binary in nature in that they are
limited to generating simple triggering alarms, such as whether a
particular characteristic is within an acceptable tolerance (e.g.,
whether a vehicle's speed is in compliance with a pre-set maximum
authorized speed).
[0010] Such binary solutions offer only temporary notice (e.g., an
audible alarm) to the driver that they are engaged in unsafe
driving behavior and when that behavior abates (e.g., the cessation
of the alarm). These solutions do not provide an indication of
long-term or habitual unsafe driving behavior and can easily be
`muted` or otherwise disabled by the driver whereby any value
offered by such an alarm solution is eliminated. These binary
solutions, too, often do not inform another party, such as a fleet
manager, of such unsafe driving behavior as the driver alone hears
the alarm and is made aware of the unsafe behavior.
[0011] High-grade digital mapping systems offering detailed,
digital models of the American highway, road, and street networks
and developed for the consumer in-vehicle navigation market have
provided an opportunity to combine map data with vehicle operation
and location data to offer innovative software based services and
solutions. Presently available digital map databases, such as those
provided by NAVTEQ, can include up to 150 individual road
attributes as well as individual points of interest, localities,
and addresses. Continuing developments in map database technology
allow for allocation of even more attributes to segments of road
data including speed limit, school and construction zone
information, car pool lane limitations including persons, and hours
of operation, prohibitions on turns (e.g., no right turn on red
between 6-9 AM), and so forth.
[0012] In the transportation industry, managers of trucking fleets
worry about their vehicles and drivers speeding on arterial and
surface streets as well as in highway construction zones in
addition to violating other traffic ordinances. Not only does such
behavior put employees and third-parties at risk, but it is also
directly proportional to the costs of insurance premiums that
result in an increase in the price of transportation services that
trickle-down to customers benefiting from delivery services. Being
able to monitor and address unsafe driving behavior would result in
a decrease of these incidents and a decrease in insurance
costs.
[0013] There presently exists no user-friendly mechanism and or
analytic tools for measuring a vehicle's and or a driver's
performance given geographic and environmental contexts of that
vehicle in determining whether that vehicle or driver is operating
outside a margin of safety.
SUMMARY OF THE INVENTION
[0014] The present invention provides a system and method for
analyzing certain vector and operational data received from a
vehicle in the form of vehicle data against map data from a
database, which includes certain road segment attributes. This
analysis allows a user to assess tendencies of a vehicle or its
operator to operate in an unsafe manner according to criteria
defined by the user.
[0015] In an exemplary embodiment, a method provides a
software-based service that combines data collected by GPS
receivers in vehicles with road speed-limit information from data
repositories, which can include data representing high-grade
digitized maps (including graphical descriptions and geographic
context characteristics describing environs of a segment of a road)
in order to monitor drivers for excessive speed. This service is an
easy-to-deploy method of predicting and identifying accident-prone
drivers before accidents happen thereby providing fleet managers
and safety experts from the insurance industry, among others, with
a relatively easy-to-use and low-cost tool for improving safety
management.
BRIEF DESCRIPTION OF THE DRAWINGS
[0016] FIG. 1 is an exemplary system in accordance with one
embodiment of the present invention.
[0017] FIG. 2A is an exemplary representation of map data
reflecting existence of various road segments.
[0018] FIG. 2B is a detailed view of road segments of FIG. 2A
wherein particular road segment attributes are shown.
[0019] FIG. 3 is a flow chart representing an exemplary method of
evaluating vehicle and or operator performance.
[0020] FIG. 4 illustrates an exemplary tabular format for reporting
analyzed vehicle data in accordance with an exemplary embodiment of
the present invention.
[0021] FIG. 5 illustrates another exemplary format for graphically
reporting analyzed vehicle data in accordance with an exemplary
embodiment of the present invention.
SUMMARY OF THE INVENTION
[0022] Detailed descriptions of exemplary embodiments are provided
herein. It is to be understood, however, that the present invention
may be embodied in various forms. Therefore, specific details
disclosed herein are not to be interpreted as limiting, but rather
as a basis for claims and as a representative basis for teaching
one skilled in the art to employ the present invention in virtually
any appropriately detailed system, structure, method, process, or
manner.
[0023] In accordance with one embodiment of the present invention,
a system and method analyzes vehicle operational data, vector data,
and location data, for example, in conjunction with information
from a map database to allow a user to assess whether a vehicle is
being operated in a potentially dangerous manner. Such a
determination can be made by ranking or rating different drivers
and or vehicles according to their propensity for potentially
dangerous operation as determined by analyzing specific sets or
subsets of data representing a driver's or a vehicle's
performance.
[0024] User inputs can define how to evaluate different drivers and
or vehicles using vehicle attribute data (e.g., weight, width,
height, length, number of axles, load type, number, and types of
occupants) and time period or trips over which driver or vehicle
should be evaluated. Each of these different drivers can be
identified with an operator identifier, which is associated with
one or more vehicle identifiers. For example, a driver having
Operator ID number 1453 can be associated with truck numbers T1,
T4, T15, and T22. Hence, the Operator 1453's driving behavior can
be evaluated over each of the vehicles (i.e., T1, T4, T15, and T22)
that the driver operates.
[0025] As described herein, vehicle data is comprised of vector
data and operational data. Vector data includes positional
information (e.g., x-y-z coordinates determined from GPS
information, such as longitude, latitude, and elevation over
sea-level), velocity information (e.g., speed, and acceleration)
and any other information derived from positional-determination
means as determined by, for example, a GPS receiver. Operational
data includes information relating to operational parameters of the
vehicle such as centrifugal force (as measured in `G's`),
rotational engine speed (as measured in `RPMs`), torque, oil
temperature, tire pressure readings, or any other sensor-generated
data.
[0026] The vector and operational data received from these vehicles
in the form of vehicle data can be collected in real-time and/or at
some point in time where data is `batched` or downloaded at certain
intervals of time (e.g., data is downloaded from a fleet vehicle
after returning to a fleet base station via infra-red or any other
communication medium). This vehicle data is then relayed to a
computer for analysis in comparison and/or contrast to map
information (e.g., road segments and road segment attributes in a
map database). The present invention also envisions a system
wherein analysis of vehicle data against map information occurs in
real-time wherein the computer and/or database are on-board with
the vehicle generating relevant vehicle data.
[0027] The matching vehicle data (e.g., vehicle speed or vehicle
weight) and the road segment attribute information (e.g., speed
limit or vehicle weight restriction) are analyzed to determine how
the vehicle's operation compares to a set of user-defined safety
criteria, for example, a set of characteristics entered by the user
to generate a report. The system and method can then rate and rank
operators and or vehicles according to their propensity to violate
predetermined rules set by the user (e.g., a fleet manager).
[0028] In accordance with a specific embodiment, vehicle data can
be collected and/or inferred (e.g., derived) from data collected by
various types of sensors including in-vehicle GPS receivers,
vehicle speedometer, and/or through external inference, such as
cell phone, satellite triangulation, or by other known means.
[0029] An exemplary method and system in accordance with the
present invention can use a map database containing road segments
and road segment attribute information. Roads (or any other
thoroughfare) are stored as data in the map database and can be
represented as a collection of road segments. Each road segment in
the database will be associated with road segment attributes that
provide information about a specific road segment such as road
type, speed limit, vehicle weight, and/or height restriction, turn
restrictions, and so forth.
DETAILED DESCRIPTION
[0030] FIG. 1 illustrates an exemplary evaluation system 100. A
processor 108 of evaluation system 100 is configured to receive
vehicle data 122 from a vehicle 124 via any one of relay 120 and
network 118. The processor 108 of evaluation system 100 is
configured to exchange map data 102 with map database 104 as well
as to exchange vehicle/operator data 128 with vehicle/operator
database 106. The processor 108 is also configured to deliver
evaluation information 130 to a client 116 via local network 114 in
response to a client request 132.
[0031] Vehicle 124 can be any type of automobile, truck, or other
conveyance such as a water-traversing vehicle. Vehicle 124
generally includes a position and or direction-determining device,
such as a Global Positioning System (GPS) receiver, and can include
additional hardware and/or software for generating, transmitting,
and/or receiving data, such as vector or operational data. While
one skilled in the art will appreciate exact operational details of
GPS, at a more fundamental level, GPS is a navigation system that
provides specially coded satellite signals that can be processed in
a GPS receiver enabling the receiver to compute position, velocity,
and time. The present invention envisions alternative embodiments
wherein other position and/or direction-determining devices (e.g.,
Dead Reckoning from Qualcomm), are utilized for generating,
transmitting, and/or receiving data, such as vector or operational
data.
[0032] In one embodiment, at least a portion of the hardware and or
software residing, in part, within vehicle 124 can function in a
manner similar to DriveRight manufactured by Davis Instruments.
DriveRight, and products like it, provide an on-board display
console for viewing time, distance, top speed, and average speed.
In particular, a portion of the hardware operates as a data port
from which vector and or operational data can be retrieved for
transmittal from vehicle 124 to processor 108 in the form of
vehicle data 122.
[0033] While present products like DriveRight do not take into
account geographic data, such as map data from a map database,
these products do use vector and/or operational data from the
vehicle's own instruments through the vehicle's On-Board Diagnostic
system ("OBD")--a computer-based system built into all model year
1996 and newer cars and trucks that monitors performance of the
vehicle's major components and emission controls--as well as
various unsafe operation sensors to to prepare vehicle data
122.
[0034] This vehicle vector and/or operation data generated by GPS
receiver and/or other resident hardware and/or software is
transmitted in the form of vehicle data 122 to processor 108 for
generating analytical reports in accordance with the present
invention. In an exemplary embodiment, vehicle data 122 is any form
of machine-readable data reflecting vehicle vector data and/or
operational data such as velocity, position, RPMs, oil temperature,
and so forth. Other hardware embodiments for generating vehicle
vector and/or operation data can include industry-standard
telemetric hardware such as @Road's FleetASAP or Qualcomm's
OmniTRACS. OmniTRACS computes position by measuring the round trip
delay of synchronized transmissions from two geostationary
satellites separated by 12-24 degrees. The network management at
the OmniTRACS hub computes the range of each satellite and derives
the third measurement needed for position from a topographic model
of the earth. These various hardware and/or software embodiments
can be implemented at the vehicle 124 and/or remotely in evaluation
system 100 as is most appropriate per design of the particular
embodiment.
[0035] Relay 120 can be any relay station for receiving and
transmitting signals between a vehicle 124 and a processor 108 of
evaluation system 100, such as an antenna, cellular phone tower, or
any other transmission tower using known or future wireless
protocols. Network 118 can be any communications network known in
the art configured to transport signals between the relay 120 and
the processor 108 of evaluation system 100 such as the Internet or
proprietary wireless networks. In some embodiments, relay 120 can
be replaced with satellites or any other suitable equivalents for
operation with the adapted network 118 for communicating vehicle
data 122 between the processor 108 and the vehicle 124.
[0036] An exemplary evaluation system 100 includes, at least, the
map database 104, the vehicle/operator database 106, and the
processor 108 comprising analysis engine 110 and report generator
112. Map database 104 and vehicle/operator database 106 can include
any data structure adapted for storage and access as generated in
accordance with exemplary methods of the present invention, and can
include optical storage media such as CD-ROM, non-volatile memory
such as flash cards, or more traditional storage structures such as
a computer hard drive.
[0037] Map database 104 is configured to store and to provide map
data 102. Map data includes road segments and road segment
attributes as defined by a user. Such road segment attributes can
include a posted speed limit, maximum vehicle weight, road type
(e.g., two-way traffic, paved, etc.), height restriction, turn
restriction (e.g., no right on red during certain time periods),
and so forth. Road segment attributes are limited only by an
ability to identify a particular segment of road--a road
segment--with some sort of empirical data or other statistical
limitation such as a speed limit.
[0038] For example, consider a road passing from point A through
point B to point C, where the posted speed transitions from 35 mph
to 55 mph at point B. The portion of the road between points A and
B is a first road segment, and similarly, the portion between point
B and C is a second road segment. Road segment attributes `35 mph`
and `55 mph` are associated with the related road segments and are
analyzed to determine whether a driver has exceeded the posted
speed limit over the road from point A to point C.
[0039] Vehicle/operator database 106 is configured to store and to
provide vehicle/operator data 128. Vehicle/operator data 128 can
comprise weight, width, height, length, number of axles, load type,
number and types of occupants for a particular vehicle as well as
speeds traveled by a particular vehicle at various times during its
scheduled deliveries. Vehicle/operator data 128, as it pertains to
a vehicle, is limited only to the extent that it is some
identifiable information about a particular vehicle.
Vehicle/operator data 128 can also include data for a particular
operator or driver such as a `name,` a `driver identifier,` or
`employee number.` Like vehicle/operator data 128 relating to a
vehicle, such data is limited as it pertains to a driver to the
extent that it need only be information about a particular driver.
Vehicle/operator database 106 also stores long-term statistical
information (e.g., vehicle/operator data 128) describing one or
more vehicles' and/or operators' vector, operational, and location
data over an extended period of time.
[0040] Processor 108 comprises the analysis engine 110 and report
generator 112. Processor 108, analysis engine 110, and report
generator 112 are configured to allow access to network 118, map
database 104, and vehicle/operator database 106. Processor 108 is
further configured to allow access by client 116. Access
configuration, in the case of the client 116, can optionally occur
via network 114. Network 114 can be a local area network or a
wide-area network. More traditional means of access configuration
to client 116 may include a bus. Any means of allowing client 116
access to processor 108 is acceptable in the present invention.
[0041] The exemplary processor 108 can be any computing device
known in the art, such as a server, central computer, or the like.
Processor 108 is able to process instructions from, at least,
analysis engine 110 and report generator 112 in addition to client
116. Processor 108 also may interact with map database 104 and
vehicle/operator database 106 to the extent it is necessary to
retrieve map data 102 and/or vehicle/operator data 128, and to
store new data to the databases 104 and 106. Processor 108 may also
receive vehicle data 122 from network 118 and or/relays 120 and to
request certain data from a vehicle 124 via the same means.
[0042] Analysis engine 110 and report generator 112 can comprise
hardware, software, or a combination thereof. Analysis engine 110
and report generator 112 may or may not be in a common housing
dependent on the nature of processor 108. Some embodiments may
configure analysis engine 110 and report generator 112 on multiple
processors 108 to allow for reduced workload on any single
processor 108 or to provide for redundancy as to allow for fault
tolerance. Any configuration is acceptable in the present invention
so long as analysis engine 110 and report generator 112 are able to
interact with various elements of the present invention, namely the
processor 108, to carry out their allocated responsibilities.
[0043] Analysis engine 110 and report generator 112 manage the
analysis and report generation process, respectively, in accordance
with an embodiment of the present invention. Client 116, in turn,
can be any variety of personal computers, workstations, or other
access devices such as a personal digital assistant (e.g., a Palm
Handheld from Palm, Inc. or the Blackberry from Research in
Motion). Client 116 need only be able to provide the necessary
input to access processor 108 and output provided by processor
108.
[0044] Analysis engine 110, specifically, is the software and or
hardware that manages the analysis of data retrieved from the
vehicle/operator database 106 and map database 104 in response to
queries from a user entering input via client 116. Such an analysis
can include any Boolean and or logical, arithmetic, mathematical,
or other operation for comparing data.
[0045] For instance, if a fleet manager wishes to determine the
performance, in terms of speed, of each driver in a fleet of
vehicles over a particular road segment, the fleet manager may
input driver IDs and a road segment identifier related to that road
segment via client 116. Analysis engine 110 causes the processor
108 to fetch map data 102 from the map database 104 representing,
at least, posted speed information (i.e., a road segment attribute)
for that road segment (e.g., a 45 mph speed limit for a specific
stretch of city street). Analysis engine 110 may also instruct
processor 108 to fetch vehicle/operator data 128 for a particular
group of drivers reflecting their average and maximum speed
traveled over the particular road segment of interest from
vehicle/operator database 106.
[0046] If, following analysis by analysis engine 110, the
vehicle/operator data 128 for a particular driver indicates driving
behavior exceeding the posted limit for a particular road segment
as identified by map data 102, an indication is generated. This
indication is included in a report generated by report generator
112. Report generator 112 is the software and/or hardware that
creates and distributes reports according to criteria set by a
user. FIGS. 4 and 5 illustrate exemplary report formats embodying
representations of some of the map data 102 and vehicle/operator
data 128 gathered by evaluation system 100. This report is
delivered to client 116 in the form of evaluation information 130.
Evaluation information 130 is machine-readable data that can be
reconstructed by client 116 in a form recognizable and
understandable to the user such as exemplified in FIGS. 4 and 5.
Reconstruction of evaluation information 130 can be manipulated as
to depend on the particular type of user interface being utilized
in client 116.
[0047] Delivery of evaluation information 130 as prepared by
analysis engine 110 and report generator 112 to client 116 can
occur through a point-to-point link such as a bus or any type of
network 114 such as a local area network (an Intranet) or a
wide-area network 114 (e.g., a wireless network, the Internet, or a
large-scale, closed proprietary network).
[0048] An alternative embodiment of the present invention provides
for processor 108, analysis engine 110, report generator 112, and
map database 104 to be located entirely within a vehicle 124 so
that driver may be notified in real-time as to whether the driver
is violating any particular road segment attribute such as speed
limit.
[0049] FIG. 2A is an exemplary embodiment of map data 102 as
retrieved from map database 104 (FIG. 1). Map data 102 is comprised
of road segments 202, 204, 206, 208, 210, 212, 214, 216, 218, 220,
and 222. Road segments are identifiable portions of road or
highway. Road segments can comprise, for example, a city block or a
particular stretch of highway between two mile markers. Road
segments can also comprise portions of road or highway with
particular or unique features such as a particular road surface
(e.g., pavement or gravel), zones (e.g., school or construction),
or lane limitations (e.g., no right turn on red or carpool
lanes).
[0050] Road segment attributes are associated with the
aforementioned road segments 202-222. Road segments attributes are
identifiable features of a particular road segment such as a posted
speed limit, hours of limited operation, weight restrictions,
specific traffic regulations, hazardous cargo requirements, and so
forth. One road segment can have multiple road segment attributes.
For example, one road segment (like a highway) can have a road
segment attribute pertaining to speed limit and another road
segment attribute as to hazardous cargo limitations.
[0051] Road segment attributes can be standard information about a
particular road segment as might be provided by a commercial
digital map producer such as car pool lane information or speed
limits. A user can also assign specific road segment attributes
through input provided by client 116 (FIG. 1) and stored in map
database 104 by the processor 108 for later access and
reference.
[0052] FIG. 2B is a detailed view of certain road segments from
FIG. 2, in particular, road segments 218, 220, and 222 and their
related road segment attributes 219, 221, and 223.
[0053] For example, road segment 218 is a particular stretch of
highway. This segment of the highway, however, is subject to a 65
mph speed limit and the existence of a car pool lane whereby only
passenger vehicles with 2 or persons are allowed to travel in the
car pool lane between the hours of 6 and 9 AM and 3 and 6 PM. These
limitations-speed limit and car pool lane hours-are the road
segment attributes 219 for road segment 218.
[0054] Road segment 220 has its own unique set of road segment
attributes 221. In this case, a particular stretch of highway has
no carpool lane limitations-all three lanes are open to all forms
of traffic-but there is presently construction on this stretch of
highway whereby the speed limit is reduced to 25 mph. The
non-existence of a carpool lane and the construction zone speed
limit are the road segment attributes 221 for this particular
highway segment.
[0055] By further example, road segment 222 has a 65 mph speed
limit, 3 lanes, and a hazardous cargo prohibition. The speed limit,
lane information, and cargo prohibition are the road segment
attributes 223 for this particular road segment 222.
[0056] A user of client 116 (FIG. 1) can access the processor 108
and request map data 102 (FIG. 1) from map database 104 (FIG. 1).
In particular, the user can request data for road segment 218 and
its related road segment attributes 219. User can then query
vehicle/operator database 106 (FIG. 1) for the driving information
of a particular vehicle and its operator on road segment 218 on a
particular date and at a particular time. Analysis engine 110 (FIG.
1) can then determine that the particular driver happened to be
driving a commercial vehicle in the carpool lane at 4.45 PM (as is
prohibited and noted in road segment attribute 219) wherein an
indication would be generated. Report generator 112 (FIG. 1) will
then report the existence of this indication to client 116 in the
form of evaluation information 130 (FIG. 1). User can then, after
review of the evaluation information 130, determine whether any
sort of warning need be provided to the driver.
[0057] If the vehicle/operator data 128 (FIG. 1) as stored in
vehicle/operator database 106 reflects an ongoing trend of
violating local traffic ordinances, this indication will also be
generated by analysis engine 110 and reported by report generator
112 in the form of evaluation information 130 to the user. The user
can then determine whether any sort of disciplinary action--such as
termination of the driver's employment--need be taken.
[0058] This type of information would, in the absence of the
present invention, be unavailable without the issuance of a
citation by local law enforcement or reporting of an illegal
traffic behavior by a concerned motorist to a customer complaint
line as is often offered through `How am I Driving?` report lines
advertised on backs of commercial trucking units.
[0059] An exemplary method for evaluating vehicle and/or operator
performance is shown in FIG. 3. The evaluation method 300 is
initiated by a client request 302 from a user of the client 116
(FIG. 1). The client request 302 is initiated with an intention of
receiving evaluation information to perform an evaluation of a
vehicle and/or driver's performance. The client request 302 can
comprise any number of variables including information concerning a
particular driver, a particular vehicle, a particular time of day,
or a particular route. The request can include real-time
information or a historical record of information as well as
performance over a particular road segment or with regard to
particular road segment attributes.
[0060] In response to a client request 302, the analysis engine 110
(FIG. 1) will make a map data request 304 via processor 108. Map
data request 304 will request specific map data 102 (FIG. 1) from a
map database 104 (FIG. 1) in accordance with the variables of
client request 302. The map data 102 retrieved from map database
104 in response to map data request 304 is determined by the scope
of the aforementioned client request 302 and can include, for
example, as little as data pertaining to a particular road segment
202 (FIG. 2A) or a larger return of data, for example, all road
segments exhibiting a particular road segment attribute 223 (FIG.
2B).
[0061] Analysis engine 110 also makes a vehicle/operator data
request 306 via processor 108 of the vehicle/operator database 106
(FIG. 1) seeking particular vehicle/operator data 128. The
vehicle/operator data request 306 is made in accordance with the
variables of the client request 302. The vehicle/operator data 128
retrieved from vehicle/operator database 106 is determined by the
scope of the aforementioned client request 302 and can include, for
example, as little as data pertaining to a particular
vehicle/driver on one day or a larger return of data, for example,
a vehicle/driver's performance over several weeks.
[0062] Retrieval of data from map database 104 and vehicle operator
database 106 by the processor 108 on behalf of the analysis engine
110 in response to a client request 302 can occur serially or in
parallel. The present invention is not limited by one field of data
being retrieved prior to the second.
[0063] Upon retrieval of data by the processor 108 on behalf of an
analysis engine 110, analysis engine 110 will perform an analysis
of the various fields of data 308 in accordance with the client
request 302. This analysis 308 can include any Boolean and/or
logical, arithmetic, mathematical, or other operation for comparing
data in response to the client request 302.
[0064] Following an analysis 308, the report generator 112 will
take the analyzed data and any indications to generate a report
310. The report is generated in accordance with criteria set by the
user in its client request 302. Such a report can include, for
example, a particular driver's highest speed along a particular
route or a particular driver's time spent traveling above the
posted speed limit (speeding) for a particular road segment. The
scope of the report generated 310 by a report generator 112 is
limited only by the scope of the client request 302 and the
available data in a map and vehicle/operator database.
[0065] Following generation of a driver/vehicle report, evaluation
information 130, often in the form of a chart or graph, is
delivered 312 by the processor 108 on behalf of the report
generator 112 to the user making the initial client request 302.
Examples of evaluation information are exemplified in FIGS. 4 and
5.
[0066] The method also allows for retrieval of real-time
vehicle/operator information concerning a particular vehicle or
driver that may not be immediately available in vehicle/operator
database 106. There can exist instances where the processor 108 is
unable to retrieve the data requested by an analysis engine 110
because the vehicle/operator data 128 is in real-time and/or has
not yet been transmitted to the processor 108 and/or stored in the
vehicle/operator database 106. In these instances, the processor
108, on behalf of analysis engine 110, can make a real-time request
314 to a particular vehicle 124 (FIG. 1) via any number of relays
120 (FIG. 1) and or network 118 (FIG. 1) as is necessary. Upon
receiving this request, the operative data-collecting component in
vehicle 124 will deliver the requested vehicle data 122 via a
real-time response 316 through any number of relays 120 and or
network 118, as is necessary, to the processor 108 and analysis
engine 110.
[0067] Processor 108 can, either serially or in parallel, store the
newly received data from the real-time response 316 via a storage
step 318 as it is being analyzed 308 by an analysis engine 110.
Completion of the evaluation method 300 would then continue via
report generation 310 and delivery of evaluation information
312.
[0068] FIG. 4 illustrates a representative format for reporting, in
a table, analyzed map and vehicle/operator data in accordance one
embodiment of the present invention. In this exemplary Fleet
Summary Report 402, a fleet manager can quickly determine a rank of
each of the drivers in a fleet. This report draws the fleet
manager's attention to potential problematic drivers who may need
closer supervision or training. Exemplary rankings include:
percentage of route speeding (404); percentage of streets speeding
(406); average speed (408); highest speed on a freeway (410);
highest speed on city streets (412); most significant speed related
incident (414); and other criterion defined by a user.
[0069] FIG. 5 illustrates another representative format for
graphically reporting analyzed map and vehicle/operator data in
accordance with one embodiment of the present invention. The
exemplary Graphical Fleet Summary Report 502 shown in FIG. 5 is
designed to draw attention to potentially dangerous incidents. This
report 502 graphically presents a detailed path of a vehicle 504,
and uses colors or any other visual representation to highlight
driver incidents 506. When the user places a computer mouse over
the path 504 a window 508 appears giving detailed information on
the corresponding incident 506. For example, after obeying the
speed limit over segment B (e.g., hence no indications to the
contrary), the driver over segment A is shown to be traveling at
112 kph in a 60 kph zone for that road segment. A user utilizing
the evaluation method exemplified in FIG. 3 can obtain this
information in real-time or post-transmission.
[0070] By utilizing the exemplary reports of FIGS. 4 and 5 or any
other report generated by the system a fleet supervisor can get a
comparative overview of all his drivers according to criteria
(pre-set or otherwise). This driver ranking report can then be used
to highlight those drivers most in need of closer supervision or
training. Insurance companies can encourage their fleet manager
clients to use the system and method to lower loss ratios or, in
other words, reduces crashes and save lives.
[0071] In addition to the report outlined in FIGS. 4 and 5, other
delivery formats such as e-mail-based reports can be used to
provide information to a user.
[0072] In some embodiments, known probabilistic approaches can be
applied to predict a vehicle's or an operator's future tendencies
because embodiments of the present invention overcomes the
shortcomings in data quality that traditional binary approaches
cannot. Importantly, exemplary methods described herein assess the
"geographic context" to telemetric reporting by taking into
account, for example, changing speed limit information. In other
embodiments, specific weather/construction conditions relating to a
specific road segment is considered in the calculus of ranking
drivers (e.g., whether it was raining at, or in the vicinity of, a
specific road segment, where such meteorological data is retrieved
from other databases containing such information).
[0073] One having ordinary skill in the art should appreciate that
the methodologies discussed herein take into account that sensor
error occurs and underlying map attribute data may be outdated or
erroneous (e.g., a speed limit may be been changed). In some
embodiments, these errors are detected or accommodated by the
system via manual updates to the map database 104 (e.g., a new
batch of map information introduced via a CD-ROM or entered
manually by hand) or, in some embodiments, by data reported by the
driver of a vehicle 124 during transmission of vehicle data 122,
which can include data pertaining to new or changed road segment
attributes. Some map databases 104 might be connected to an outside
network (not shown) to automatically obtain new map data 102 via an
Internet connection to a third-party server providing regularly
updated map data 102.
[0074] Additionally, more than one type of underlying map database
104 can used to adapt to differences in sets of map data 102 and be
used to test the effect of map quality on the report results as
maps from some providers contain more attribute error than
others.
[0075] In some embodiments, a database can be used to provide
information regarding trip time, location, weather, congestion,
road construction, types of cargo, etc. to refine the data
collected to generate more meaningful reports. That said, an
exemplary report in accordance with the present invention could
highlight specific incidents and can have a strong deterrent effect
and discourage irresponsible driving habits when used by a fleet
manager as part of a safety program.
[0076] In other embodiments, additional report elements outlined
above can further include inferred vector versus reported vector.
Most in-vehicle GPS receivers calculate and record speed but some
only record latitude and longitude. The present invention may infer
latitude and longitude from speed.
[0077] The above description is illustrative and not restrictive.
Many variations of the present invention will become apparent to
those of skill in the art upon review of this disclosure. The scope
of the present invention should, therefore, be determined not with
reference to the above description, but instead should be
determined with reference to the appended claims along with their
full scope of equivalents.
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